PhD defence
Optimizing Solvers for Real-World Expensive Black-Box Optimization with Applications in Vehicle Design
- F.X. Long
- Date
- Thursday 27 November 2025
- Time
- Location
-
Academy Building
Rapenburg 73
2311 GJ Leiden
Supervisor(s)
- Prof.dr. T.H.W. Bäck
- Prof.dr.Ing. M. Gitterle
Summary
Optimally solving real-world expensive Black-Box Optimization (BBO) problems w.r.t. real-world constraints, such as wall-clock time and computational costs, is extremely difficult and tedious. Automotive crashworthiness optimization using expensive Finite Element (FE) simulations in the automotive industry, for instance, is a representative example of real-world BBO problems, which is typically highly nonlinear, discontinuous, and high-dimensional.
Within the scope of this thesis, we investigate an automated optimization approach for optimally solving real-world expensive BBO problems using a limited function evaluation budget. By exploiting some cheap-to-evaluate representative functions that belong to the same optimization problem classes as the BBO problems to-be-solved, nearly optimal optimization configurations can be identified at a relatively low computational expense, e.g., using Hyperparameter Optimization (HPO), prior to the actual optimization runs using expensive function evaluations. Eventually, the expensive BBO problems can be efficiently solved using the fine-tuned optimization configurations. W
hen evaluated on the Black-Box Optimization Benchmarking (BBOB) suite, we can identify better performing optimization configurations than the default configuration using the proposed optimization approach. Remarkably, the optimal optimization configurations are even competitive against the Single Best Solver (SBS) on some BBOB functions. More importantly, the Bayesian Optimization (BO) configurations fine-tuned using our approach can outperform the state-of-the-art Response Surface Method (RSM) for solving an automotive side crash problem in terms of the best-found-solution and convergence speed. In conclusion, our results show that the proposed automated optimization pipeline has an encouraging potential for an efficient solving of real-world expensive BBO problems, such as vehicle design problems.
PhD dissertations
Approximately one week after the defence, PhD dissertations by Leiden PhD students are available digitally through the Leiden Repository, that offers free access to these PhD dissertations. Please note that in some cases a dissertation may be under embargo temporarily and access to its full-text version will only be granted later.
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